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So let's look at the vision that Tim
Berners-Lee [UNKNOWN] way back in 2000

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called the semantic web, which essentially
puts together some of the ideas that we

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have been talking in the past few minutes.
So to answer a, a question or query like ,

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who is the leader of USA, a semantic web
system or web intelligent system

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incorporating semantics would proceed
something like as follows: we might

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imagine a site a.com which collects facts
by processing lots of web data,

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As we shall see later in this week how
that's done. So we get facts like Obama is

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President of U.S.A., Vladimir Putin is
president of Russia, Pranab Mukherjee is

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president of India, Manmohan Singh is
Prime Minister of India, and many other

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facts about presidents, premiers, prime
ministers, etc.

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Another site might be extracting
information about who is leader of which

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country might figure out that Manmohan
Singh is leader of India, Zuma is leader

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of South Africa, Putin is leader of
Russia, and so on.

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A third site now might combine.
Facts from a.com and b.com, and come to a

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conclusion using rule earning that with
some degree of confidence that if x is the

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president of c, than x is leader of c.
The process by which a bunch of facts is

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generalized to a rule using techniques
like rule mining that we have seen earlier

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is called inductive reasoning, as opposed
to deductive reasoning, which is normal

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logical inference.
Inductive reasoning is almost always

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probabilistic to a certain extent.
Using some of the techniques that we've

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already seen.
Next normal deductive reasoning allows us

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to combine the rules and facts to arrive
at.

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The fact that Obama is the leader of the
U.S.A., which is then the answer to our

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query.
Further, this new fact is then added back

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to the appropriate part of the semantic
way of dealing with facts of this nature.

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Now this vision, is a powerful vision
expressed more than a decade ago.

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It's not exactly been realized today, but,
much of the technology needed, to express

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facts and rules, in a form that can be
shared, across, different, systems.

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Using XML languages such as RDFS, RD, we
just call it RDF schema, and OWL or the

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Web Ontology Language.
That technology has been developed by the

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World Wide Web Foundation, where Tim
Berners-Lee plays an important role.

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So the web of data and semantics is in
principle possible.

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The question is, who is populating this
web.

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Web scale inference is in some sense also
possible,

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Not necessarily happening in exactly the
same way as initially envisioned.

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But is happening.
With efforts such as Google Squared, if

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you just figured this out from the web.
It's essentially Google's attempt to

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extract lots of different facts from the
wide, the world wide web.

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Wolfram Alpha is another recent search
engine which relies on learning lots of

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facts about the world.
And, of course, there's Watson which we've

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come across earlier , the IBM program that
won the Jeopardy challenge.

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These are efforts which don't necessarily
use techniques like OWL and semantic web

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technologies.
Though they have a similar intent in

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spirit, which is essentially to learn
facts from the web and be able to reason

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about those facts in a web intelligence
system, as opposed to merely searching for

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web pages.
So to summarize, the Symantec web vision

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is about a web of data and semantics.
Which is shared so that one can have

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inference or reasoning at web scale.
A bunch of technologies which is designed

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to enable this, RDF or Resource
Description Framework as it's expansion is

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the Web Ontology Language and various
variance of that, as we can see very soon.

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These are all technologies designed to
enable this sharing of data and semantics

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across the web.
At the same time,

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They are use to actually perform
reasoning, has not necessarily proceeded

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in exactly the same way as originally
envisioned.

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Google Squared, Wolfram Alpha, Watson do
in fact reason using facts learned from

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the web, but not necessarily using the
same technology backbone.

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We shall return to the semantic web and
some efforts which are in fact learning

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facts in RDF and OWL form a little later.
For the moment let's turn to resolution

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and logic and how such deductive reasoning
might actually take place within a

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semantic web engine, regardless of the
exact technology it uses.
